title: Fault diagnosis engineering of digital circuits can identify vulnerable molecules in complex cellular pathways.
abstract: The application of complex system engineering approaches to cell signaling networks should lead to novel understandings and, subsequently, new treatments for complex disorders. In the area of circuit fault diagnosis engineering, there are various methods to identify the defective or vulnerable components of complex digital electronic circuits. In biological systems, however, knowledge is limited regarding the vulnerability of interconnected signaling pathways to the dysfunction of each specific molecule. By developing proper biologically driven digital vulnerability assessment methods, the vulnerability of complex signaling networks to the possible dysfunction of each molecule can be determined. To show the utility of this approach, we analyzed three well-characterized signaling networks--a cellular network that regulates the activity of caspase3, a network that regulates the activity of p53, and a central nervous system network that regulates the activity of the transcription factor CREB (adenosine 3',5'-monophosphate response element-binding protein). We found important differences among the vulnerability values of different molecules. Most of the identified highly vulnerable molecules are functionally related and known key regulators of these networks. Experimental data confirmed the ability of digital vulnerability assessment to correctly predict key regulators in the CREB network. Because this approach may provide insight into key molecules that contribute to human diseases, it may aid in the identification of critical targets for drug development.
authors.affiliation: Center for Wireless Communications and Signal Processing Research, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, 323 King Boulevard, Newark, NJ 07102, USA.
authors.forename: Ali
authors.initials: A
authors.lastname: Abdi
authors.forename: Mehdi Baradaran
authors.initials: MB
authors.lastname: Tahoori
authors.forename: Effat S
authors.initials: ES
authors.lastname: Emamian
mesh_terms: D000465:Algorithms; D000818:Animals; D050882:CREB-Binding Protein / Q000378:metabolism; D002478:Cells, Cultured; D008954:Models, Biological; D051381:Rats; D017207:Rats, Sprague-Dawley; D015398:Signal Transduction / Q000502:physiology*; D014158:Transcription, Genetic / Q000502:physiology*; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D016159:Tumor Suppressor Protein p53; D050882:CREB-Binding Protein; C494365:Crebbp protein, rat